Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

Identification of lactic acid bacteria strains modulating incretin hormone secretion and gene expression in enteroendocrine cells

Glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP) are incretin hormones released from intestinal enteroendocrine (EE) cells and have well-established glucose-lowering actions. Lactic acid bacteria (LAB) colonise the human intestine, but it is unknown whether LAB and EE cells interact. Acute co-culture of LAB with EE cells showed that certain LAB strains elicit GLP-1 and GIP secretion (13-194-fold) and upregulate their gene expression. LAB-induced incretin hormone secretion did not appear to involve nutrient mechanisms, nor was there any evidence of cytolysis. Instead PCR array studies implicated signalling agents of the toll-like receptor system, e.g. adaptor protein MyD88 was decreased 23-fold and cell surface antigen CD14 was increased 17-fold. Mechanistic studies found that blockade of MyD88 triggered significant GLP-1 secretion. Furthermore, blocking of CD14 completely attenuated LAB-induced secretion. A recent clinical trial clearly shows that LAB have potential for alleviating type 2 diabetes, and further characterisation of this bioactivity is warranted.

Gene expression and epigenetic discovery screen reveal methylation of SFRP2 in prostate cancer

Aberrant activation of Wnts is common in human cancers, including prostate. Hypermethylation associated transcriptional silencing of Wnt antagonist genes SFRPs (Secreted Frizzled-Related Proteins) is a frequent oncogenic event. The significance of this is not known in prostate cancer. The objectives of our study were to (i) profile Wnt signaling related gene expression and (ii) investigate methylation of Wnt antagonist genes in prostate cancer. Using TaqMan Low Density Arrays, we identified 15 Wnt signaling related genes with significantly altered expression in prostate cancer; the majority of which were upregulated in tumors. Notably, histologically benign tissue from men with prostate cancer appeared more similar to tumor (r = 0.76) than to benign prostatic hyperplasia (BPH; r = 0.57, p < 0.001). Overall, the expression profile was highly similar between tumors of high (≥ 7) and low (≤ 6) Gleason scores. Pharmacological demethylation of PC-3 cells with 5-Aza-CdR reactivated 39 genes (≥ 2-fold); 40% of which inhibit Wnt signaling. Methylation frequencies in prostate cancer were 10% (2/20) (SFRP1), 64.86% (48/74) (SFRP2), 0% (0/20) (SFRP4) and 60% (12/20) (SFRP5). SFRP2 methylation was detected at significantly lower frequencies in high-grade prostatic intraepithelial neoplasia (HGPIN; 30%, (6/20), p = 0.0096), tumor adjacent benign areas (8.82%, (7/69), p < 0.0001) and BPH (11.43% (4/35), p < 0.0001). The quantitative level of SFRP2 methylation (normalized index of methylation) was also significantly higher in tumors (116) than in the other samples (HGPIN = 7.45, HB = 0.47, and BPH = 0.12). We show that SFRP2 hypermethylation is a common event in prostate cancer. SFRP2 methylation in combination with other epigenetic markers may be a useful biomarker of prostate cancer.

IGFBP7 promoter methylation and gene expression analysis in prostate cancer

PURPOSE: IGFBP7 belongs to a family of insulin-like growth factor-1 regulatory binding proteins. IGFBP7 hypermethylation is associated with its down-regulation in various carcinomas. In prostate cancer IGFBP7 down-regulation has been widely reported but to our knowledge the mechanisms behind this event are unknown. We performed a denaturing high performance liquid chromatography screening and validation strategy to profile the methylation status of IGFBP7 in prostate cancer.

MATERIALS AND METHODS: We combined denaturing high performance liquid chromatography and bisulfite sequencing to examine IGFBP7 methylation in a panel of prostate cancer cell lines. Quantitative methylation specific polymerase chain reaction was used to determine methylation levels in prostate tissue specimens of primary prostate cancer, histologically benign prostate adjacent to tumor, high grade prostatic intraepithelial neoplasia and benign prostatic hyperplasia. IGFBP7 gene expression was measured by quantitative methylation specific polymerase chain reaction in cell lines and tissue specimens.

RESULTS: IGFBP7 was methylated in the 4 prostate cancer cell lines DU145, LNCaP, PC-3 and 22RV1. Quantitative methylation specific polymerase chain reaction analysis revealed that promoter methylation was associated with decreased IGFBP7 expression. Quantitative methylation specific polymerase chain reaction showed that IGFBP7 methylation was more frequently detected in prostate cancer (60% (31/52)) and high grade prostatic intraepithelial neoplasia (40% (6/15)) samples compared to histologically benign prostate adjacent to tumor (10%) and benign prostatic hyperplasia (0%) samples.

CONCLUSIONS: To our knowledge this is the first report of aberrant IGFBP7 promoter hypermethylation and concurrent IGFBP7 gene silencing in prostate cancer cell lines. Results demonstrate that CpG methylation of IGFBP7 may represent a novel biomarker of prostate cancer and pre-invasive neoplasms. Thus, future examination of IGFBP7 methylation and expression in a larger patient cohort, including bodily fluids, is justified to further evaluate its role in a diagnostic and prognostic setting.

Molecular Medicine and Molecular Pathology for Haematologists:I. Gene Speak made Easy: An Overview of Genes and Gene Expression

Molecular Medicine and Molecular Pathology are integral parts of Haematology as we enter the new millennium. Their origins can be linked to fundamental developments in the basic sciences, particularly genetics, chemistry and biochemistry. The structure of DNA and the genetic code that it encrypts are the critical starting points to our understanding of these new disciplines. The genetic alphabet is a simple one, consisting of just 4 letters, buts its influence is crucial to human development and differentiation. The concept of a gene is not a new one but the Human Genome Project (a joint world-wide effort to characterise our entire genetic make-up) is providing an invaluable understanding of how genes function in normal cellular processes and pinpointing how disruption of these processes can lead to disease. Transcription and translation are the key events by which our genotype is converted to our phenotype (via a messenger RNA intermediate), producing the myriad proteins and enzymes which populate the cellular factory of our body. Unlike the bacterial or prokaryotic genome, the human genome contains a large amount of non coding DNA (less than 1% of our genome codes for proteins), and our genes are interrupted, with the coding regions or exons separated by non coding introns. Precise removal of the intronic material after transcription (though a process called splicing) is critical for efficient translation to occur. Incorrect splicing can lead to the generation of mutant proteins, which can have a dilaterious effect on the phenotype of the individual. Thus the 100,000-200,000 genes which are present in each cell in our body have a defined control mechanism permitting efficient and appropriate expression of proteins and enzymes and yet a single base change in just one of those genes can lead to diseases such as haemophilia or fanconis anaemia.

Characterization of a reference material for BCR-ABL (M-BCR) mRNA quantitation by real-time amplification assays:towards new standards for gene expression measurements

Monitoring of BCR-ABL transcripts has become established practice in the management of chronic myeloid leukemia. However, nucleic acid amplification techniques are prone to variations which limit the reliability of real-time quantitative PCR (RQ-PCR) for clinical decision making, highlighting the need for standardization of assays and reporting of minimal residual disease (MRD) data. We evaluated a lyophilized preparation of a leukemic cell line (K562) as a potential quality control reagent. This was found to be relatively stable, yielding comparable respective levels of ABL, GUS and BCR-ABL transcripts as determined by RQ-PCR before and after accelerated degradation experiments as well as following 5 years storage at -20 degrees C. Vials of freeze-dried cells were sent at ambient temperature to 22 laboratories on four continents, with RQ-PCR analyses detecting BCR-ABL transcripts at levels comparable to those observed in primary patient samples. Our results suggest that freeze-dried cells can be used as quality control reagents with a range of analytical instrumentations and could enable the development of urgently needed international standards simulating clinically relevant levels of MRD.

Achieving hypoxia-inducible gene expression in tumors

Hypoxia is an inevitable feature of solid tumors and a common cause of treatment failure. Hypoxia acts as a trigger to genetic instability, apoptosis and possibly metastases. The adaptive response to cellular hypoxia involves the modulation of the synthesis of multiple proteins controlling processes such as glucose homeostasis, angiogenesis, vascular permeability and inflammation. The hypoxia responsive element (HRE) sequences isolated from oxygen-responsive genes have been shown to selectively induce gene expression in response to hypoxia when placed upstream of a promoter. The levels of induced gene expression were dependent on the number of HRE copies and the oxygen tension. Hypoxia-mediated cancer gene therapy strategies may represent a promising mean to significantly improve the efficacy of standard radiation therapy and chemotherapy approaches.

Integrative analysis of chemo-transcriptomic profiles for drug-feature specific gene expression signatures

One of the major challenges in systems biology is to understand the complex responses of a biological system to external perturbations or internal signalling depending on its biological conditions. Genome-wide transcriptomic profiling of cellular systems under various chemical perturbations allows the manifestation of certain features of the chemicals through their transcriptomic expression profiles. The insights obtained may help to establish the connections between human diseases, associated genes and therapeutic drugs. The main objective of this study was to systematically analyse cellular gene expression data under various drug treatments to elucidate drug-feature specific transcriptomic signatures. We first extracted drug-related information (drug features) from the collected textual description of DrugBank entries using text-mining techniques. A novel statistical method employing orthogonal least square learning was proposed to obtain drug-feature-specific signatures by integrating gene expression with DrugBank data. To obtain robust signatures from noisy input datasets, a stringent ensemble approach was applied with the combination of three techniques: resampling, leave-one-out cross validation, and aggregation. The validation experiments showed that the proposed method has the capacity of extracting biologically meaningful drug-feature-specific gene expression signatures. It was also shown that most of signature genes are connected with common hub genes by regulatory network analysis. The common hub genes were further shown to be related to general drug metabolism by Gene Ontology analysis. Each set of genes has relatively few interactions with other sets, indicating the modular nature of each signature and its drug-feature-specificity. Based on Gene Ontology analysis, we also found that each set of drug feature (DF)-specific genes were indeed enriched in biological processes related to the drug feature. The results of these experiments demonstrated the pot- ntial of the method for predicting certain features of new drugs using their transcriptomic profiles, providing a useful methodological framework and a valuable resource for drug development and characterization.

Meta-analysis of prostate cancer gene expression data identifies a novel discriminatory signature enriched for glycosylating enzymes

BACKGROUND: Tumorigenesis is characterised by changes in transcriptional control. Extensive transcript expression data have been acquired over the last decade and used to classify prostate cancers. Prostate cancer is, however, a heterogeneous multifocal cancer and this poses challenges in identifying robust transcript biomarkers.

METHODS: In this study, we have undertaken a meta-analysis of publicly available transcriptomic data spanning datasets and technologies from the last decade and encompassing laser capture microdissected and macrodissected sample sets.

RESULTS: We identified a 33 gene signature that can discriminate between benign tissue controls and localised prostate cancers irrespective of detection platform or dissection status. These genes were significantly overexpressed in localised prostate cancer versus benign tissue in at least three datasets within the Oncomine Compendium of Expression Array Data. In addition, they were also overexpressed in a recent exon-array dataset as well a prostate cancer RNA-seq dataset generated as part of the The Cancer Genomics Atlas (TCGA) initiative. Biologically, glycosylation was the single enriched process associated with this 33 gene signature, encompassing four glycosylating enzymes. We went on to evaluate the performance of this signature against three individual markers of prostate cancer, v-ets avian erythroblastosis virus E26 oncogene homolog (ERG) expression, prostate specific antigen (PSA) expression and androgen receptor (AR) expression in an additional independent dataset. Our signature had greater discriminatory power than these markers both for localised cancer and metastatic disease relative to benign tissue, or in the case of metastasis, also localised prostate cancer.

CONCLUSION: In conclusion, robust transcript biomarkers are present within datasets assembled over many years and cohorts and our study provides both examples and a strategy for refining and comparing datasets to obtain additional markers as more data are generated.

Histone deacetylase inhibitors suppress thymidylate synthase gene expression and synergize with the fluoropyrimidines in colon cancer cells

Despite recent therapeutic advances, the response rates to chemotherapy for patients with metastatic colon cancer remain at approximately 50% with the fluoropyrimidine, 5-fluorouracil (5-FU), continuing to serve as the foundation chemotherapeutic agent for the treatment of this disease. Previous studies have demonstrated that overexpression of thymidylate synthase (TS) is a key determinant of resistance to 5-FU-based chemotherapy. Therefore, there is a significant need to develop alternative therapeutic strategies to overcome TS-mediated resistance. In this study, we demonstrate that the histone deacetylase inhibitors (HDACi) vorinostat and LBH589 significantly downregulate TS gene expression in a panel of colon cancer cell lines. Downregulation of TS was independent of p53, p21 and HDAC2 expression and was achievable in vivo as demonstrated by mouse xenograft models. We provide evidence that HDACi treatment leads to a potent transcriptional repression of the TS gene. Combination of the fluoropyrimidines 5-FU or FUdR with both vorinostat and LBH589 enhanced cell cycle arrest and growth inhibition. Importantly, the downstream effects of TS inhibition were significantly enhanced by this combination including the inhibition of acute TS induction and the enhanced accumulation of the cytotoxic nucleotide intermediate dUTP. These data demonstrate that HDACi repress TS expression at the level of transcription and provides the first evidence suggesting a direct mechanistic link between TS downregulation and the synergistic interaction observed between HDACi and 5-FU. This study provides rationale for the continued clinical evaluation of HDACi in combination with 5-FU-based therapies as a strategy to overcome TS-mediated resistance.

A coactivator role of CARM1 in the dysregulation of β-catenin activity in colorectal cancer cell growth and gene expression

Aberrant activation of Wnt/β-catenin signaling, resulting in the expression of Wnt-regulated oncogenes, is recognized as a critical factor in the etiology of colorectal cancer. Occupancy of β-catenin at promoters of Wnt target genes drives transcription, but the mechanism of β-catenin action remains poorly understood. Here, we show that CARM1 (coactivator-associated arginine methyltransferase 1) interacts with β-catenin and positively modulates β-catenin-mediated gene expression. In colorectal cancer cells with constitutively high Wnt/β-catenin activity, depletion of CARM1 inhibits expression of endogenous Wnt/β-catenin target genes and suppresses clonal survival and anchorage-independent growth. We also identified a colorectal cancer cell line (RKO) with a low basal level of β-catenin, which is dramatically elevated by treatment with Wnt3a. Wnt3a also increased the expression of a subset of endogenous Wnt target genes, and CARM1 was required for the Wnt-induced expression of these target genes and the accompanying dimethylation of arginine 17 of histone H3. Depletion of β-catenin from RKO cells diminished the Wnt-induced occupancy of CARM1 on a Wnt target gene, indicating that CARM1 is recruited to Wnt target genes through its interaction with β-catenin and contributes to transcriptional activation by mediating events (including histone H3 methylation) that are downstream from the actions of β-catenin. Therefore, CARM1 is an important positive modulator of Wnt/β-catenin transcription and neoplastic transformation, and may thereby represent a novel target for therapeutic intervention in cancers involving aberrantly activated Wnt/β-catenin signaling.